Programme Educational Objectives & Program Outcomes
Programme Educational Objectives
PEO 1 – Core Competence and Technical Expertise
Graduates will apply advanced mathematical and computational principles to design, develop, and deploy intelligent systems using emerging technologies across multidisciplinary domains.
PEO 2 – Innovation, Research, and Lifelong Learning
Graduates will engage in innovation, research, and continuous learning, adapting to the evolving trends in AI, data science, and automation, while contributing to knowledge creation and Interdisciplinary Collaboration.
PEO 3 – Professionalism and Ethical Responsibility
Graduates will exhibit professional ethics, integrity, and social responsibility in developing and applying AI technologies, ensuring fairness, accountability, and transparency in the development of trustworthy and bias-free AI systems.
PEO 4 – Societal Impact and Entrepreneurship
Graduates will leverage AI and ML knowledge to address societal challenges, promote sustainability, and demonstrate entrepreneurial and leadership capabilities that foster innovation, community well-being and global changes.
Program Outcomes
PO1- Engineering Knowledge :
Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
PO2 : Problem Analysis :
Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences
PO3 : Design/Development of Solutions :
Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations
PO4: Conduct Investigations of Complex Problems :
Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions
PO5: Modern Tool Usage :
Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations
PO6: The Engineer and Society :
Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice
PO7: Environment and Sustainability :
Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development
PO8: Ethics :
Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice
PO9: Individual and Team Work :
Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings
PO10: Communication :
Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions
PO11 : Project Management and Finance :
Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments
PO12 : Life-long Learning :
Recognize the need for, and have the preparation and ability to engage in independent and lifelong learning in the broadest context of technological change
Program Specific Outcomes
PSO 1: Artificial Intelligence Systems & Intelligent Applications (AI Focus)
Graduates will be able to design and implement intelligent systems using core Artificial Intelligence concepts- such as knowledge representation, reasoning, search techniques, intelligent agents, and AI-based decision-making to develop smart applications in areas like automation, smart cities, robotics, and healthcare.
PSO 2: Machine Learning Models & Data Analytics (ML Focus)
Graduates will be able to build, train, evaluate, and optimize Machine Learning models using supervised, unsupervised, and deep learning techniques, apply statistical and data analytics methods, and deploy ML solutions for predictive analysis, pattern recognition, and real-world problem- solving.
PSO 3: Computer Science Foundations & Software Engineering (CSE Focus)
Graduates will be able to apply strong computer science fundamentals- including programming, data structures, algorithms, operating systems, databases, computer networks, and software engineering principles to develop secure, scalable, and efficient software systems that support AI–ML applications.